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SoDM Masters Theses School of Dental Medicine

6-1-2007 The mplicI ation of Small-Interfering RNA (siRNA) for Inhibition of LPS-Induced Osteoclast Formation and Cytokine Stimulation Farshid S. Fahid

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Recommended Citation Fahid, Farshid S., "The mpI lication of Small-Interfering RNA (siRNA) for Inhibition of LPS-Induced Osteoclast Formation and Cytokine Stimulation" (2007). SoDM Masters Theses. 150. https://opencommons.uconn.edu/sodm_masters/150 The Implication of Small-Interfering RNA (siRNA) for Inhibition of LPS­ Induced Osteoclast Formation and Cytokine Stimulation

Farshid S. Fahid

B.S., University of Los Angeles, California (UCLA), 1999 D.D.S., University of Southern California (USC), 2003

A Thesis Submitted in Partial Fulfillment of the Requirements for the Degree of Master of Dental Science at the University of Connecticut 2007

APPROVAL PAGE

Master of Dental Science Thesis

The Implication of Small-Interfering RNA (siRNA) for Inhibition of LPS­ Induced Osteoclast Formation and Cytokine Stimulation

Presented by Farshid S. Fahid, B.S., D.D.S.

MajOrAdVisor______~~ __· __ ~______Jin Jiang, D.D.S., Ph.D.

Associate Advisor_____ ;(_ ...... , _' _~_...:::...-t.:....'It_r_fI7_\ ____. ___ _ Kamran E. Safavi, D.M.D., M. Ed.

Associate Advisor__ d..;:=-:.~_."..,( __ d-_·t--=' ~;...... ;;...~ ______Frank Nichols, D.D.S., Ph.D.

University of Connecticut 2007

11 Dedicated

To My Loving Wife

8eyoona

111 TABLE OF CONTENTS

Introduction ...... 1

Review of Literature ...... 4

Etiology of Apical Periodontitis ...... 4

Studies on Endodontic Flora and Routes of Entry ...... 5

Bacterial Endotoxin-Lipopolysaccharide (LPS) ...... 8 Structure ...... 8 O-specific Chain (O-antigen) ...... 10 Core Region ...... 11 Lipid A ...... 12 Host Response ...... 13 Implication in Endodontic Infections ...... 14 Host Recognition of LPS ...... 16 The LPS Receptor Complex ...... 17 LPS Signaling Through TLR4 ...... 23

Regulation of Osteoclast Formation ...... 25 RANK Signaling in Osteoclast Differentiation ...... 27 NFATc1 ...... 29

RNA Interference (RNAi) ...... 30 Mechanism ...... 32 Design of Effective siRNA Proves ...... 33 Delivery Strategies of siRNA...... 34 Therapeutic Potential of RNAi...... 35 Aim of Study ...... 36

Material and Methods ...... 37

Results ...... 43

IV Discussion ...... 55

Conclusion ...... 68

Statistical Analysis ...... 69

References ...... 79

v Introduction

The importance of the relationship between bacteria and the pathogenesis of pulpal and periradicular disease has been well established by numerous studies (Kakehashi et ai, 1965; Sundqvist, 1976; Patterson, 1976; Moller, 1981).

Pulpal infections initially produce an inflammatory response within the pulp that often leads to complete pulpal necrosis and subsequently, in the periapical region, which results in lesion formation with local bone destruction (Bergenholtz,

1990). The bacteria from infected root canals have been extensively studied and shown to be predominantly gram-negative and strictly anaerobic (Fabricius,

1982; Farber and Seltzer, 1988). Bacterial lipopolysaccharide (LPS) is an endotoxin and a major component of the outer membrane of gram-negative bacteria. It is a complex glycolipid composed of a hydrophilic polysaccharide moiety and a hydrophobic domain known as Lipid A. It is also one of the most potent microbial initiators of inflammation (Raetz, 1990; Cohen 2002) and endodontic pathogenesis (Dwyer and Torabinejad, 1981). A positive correlation has been reported between the levels of LPS in root canals and the presence of periapical lesions (Dahlen and Bergenholtz, 1980; Schonfeld et a/1982).

Cells of the host's immune response system may detect and respond to bacteria and their byproducts. Although these products have structural sequences that are unique to strain and species specific variations, they also have a highly conserved and common molecular pattern that does not vary between microbes. This is called the pathogen associated molecular pattern

1 (PAMP) (Janeway, 1989). LPS represents the PAMP in gram-negative bacteria and the Lipid A segment is the invariant portion that is responsible for its pro­ inflammatory effects. Host immune cells recognize PAMP through a family of proteins known as Toll-like receptors (TLRs) which are an essential part of the recognition and signaling component of the mammalian host defense system

(Akira, 2001). Human TLR4 was the first TLR to be described. It is predominantly expressed in immune cells, and has now been established as the receptor for LPS (Medzhitov et aI, 1997). Once LPS passes through the apical foramen and into the periradicular tissue where it binds its receptor, it starts a cascade that leads to NF-kB activation of numerous inflammatory genes that result in cytokine production, which subsequently initiate and sustain many of the bone osteolytic events in endodontic disease (Stashenko, 1998). It has been shown that LPS can directly stimulate osteoblasts to express RANKL, resulting in osteoclast formation (Kikuchi et aI, 2001). Recent findings have also indicated that LPS may be directly involved in osteoclast differentiation (Suda et al., 2002;

Jiang et al., 2006). NFATc1 has been shown to be a key regulator of osteoclastogenesis and plays a critical role in the terminal differentiation of osteoclasts (Takayanagi et al., 2002). Once differentiated and activated, mature osteoclasts can act to resorb bone in this specialized microenvironment resulting in apical lesion formation (Dahlen, 1981).

Researchers have identified a series of cytokines that are produced by both inflammatory and non-inflammatory host cells that are involved in the bone resorptive process (Stashenko, 1994; Fouad, 1997; Stashenko, 1998). These

2 cytokines include IL-1a, IL-1j3, TNF-a, IL-6, and IL-11 (Stashenko, 1994;

Manolagas, 1995; Kawashima and Stashenko, 1999). It has also been demonstrated that when an infected root canal is thoroughly cleaned and debrided, rendering it free from bacteria and bacterial byproducts, pulpal and periapical inflammatory responses cease to occur and the damaged tissues heal themselves (Moller et aI, 1981).

RNA interference (RNAi) is emerging as a new and potent method of gene silencing that selectively targets and shuts off the post-transcriptional expression of mRNA (Elbashir et al., 2001). In an effort to determine the implication of small interfering RNAs (siRNAs) for the inhibition of LPS-induced osteoclast formation and cytokine stimulation, the objective of this study was to suppress TLR4 or

NFATc1 expression in monocytes and osteoclast cells using the RNAi technique.

We hypothesized that knocking down the expression of TLR4 and NFATc1 in these cells with effective siRNA will modulate the effects of LPS stimulation.

Thus, this study aimed to provide a potential therapeutic approach and open new horizons in the field of endodontic research.

3 Review of Literature

Etiology of Apical Periodontitis

Apical periodontitis is a local inflammatory destruction of the bone and periodontium around the apex of a tooth in response to an infection of endodontic origin (Moller et al. 2004). Although chemical and physical factors can also induce a peri radicular inflammatory response, evidence for the essential role of microbial agents in dental pulp infection and the pathogenesis of apical periodontitis is overwhelming and well-established (Kakehashi, 1965; Sundqvist,

1976; Moller, 1981).

The presence of bacteria in the necrotic dental pulp of teeth with associated pathologic conditions was reported more than a century ago, when

Miller {1894} hypothesized that microorganisms are the causative agents of endodontic disease (Miller, 1894). However, it was not until a half century later, when the causal relationship between periapical inflammation and bacterial infection was convincingly demonstrated. In the classic study by Kakehashi et al.

{1965}, it was shown that pulpal necrosis and periapical inflammation developed in rats subjected to mechanical pulp exposure and kept exposed to the conventional microbial environment of the oral cavity. Conversely, germ-free animals demonstrated minimal pulpal inflammation and no periapical destruction, and formed reparative dentin at the exposure sites, exhibiting the substantial healing capability of the pulp in the absence of infection (Kakehashi 1965).

Subsequent animal and human studies confirmed the cause and effect relationship between pulpal infection and periapical pathology.

4 In his thesis, Sundqvist (1976) observed 32 traumatized incisors with pulpal necrosis, yet clinically intact crowns. Eighteen of the 19 (95%) teeth with associated periapical lesions presented with positive cultures for bacteria that were predominantly strict anaerobes, whereas no bacteria were cultivated from the 13 teeth without periapical lesions (Sundqvist, 1976). In a controlled monkey experiment in which the pulps of 26 teeth were rendered necrotic under sterile conditions and immediately sealed in the uninfected root canal, none developed apical periodontitis, even after 6-7 months of observation. In contrast, 47 of the

52 (90%) teeth in which the pulps were deliberately infected prior to sealing of the access opening, exhibited periapical destruction (Moller et al., 1981). This study demonstrated that apical periodontitis can not be caused by necrotic pulp tissue per se, via toxic tissue breakdown products, but that the presence of bacteria within the pulp appears to be an absolute requirement for the development of periradicular disease.

Studies on Endodontic Flora and Routes of Entry

There are several pathways by which microorganisms may gain entry into the dental pulp. The most common may be through openings in the dental hard tissues as a result of the caries process, operative procedures, and trauma­ induced micro-cracks. Anachoresis, which is the transport of microorganisms via blood circulation to the area where they establish an infection, has also been proposed in cases where teeth with necrotic pulps and clinically intact crowns were observed (Robinson and Boling, 1941; Gier and Mitchel, 1968). However,

5 this theory remains controversial and the extent to which this may occur is unknown (Oelivanis and Fan, 1984). Another possible pathway for bacterial invasion and infection of the pulp may be through exposed dentinal tubules or accessory canals found at the cervical root surface in the periodontal pocket, although the importance of this pathway has also been debated (Seltzer et al.,

1963; Mazur and Massier, 1964).

Over 500 bacterial species are currently recognized as normal inhabitants of the oral cavity and an additional 200 may still be detected by molecular methods (Moore and Moore, 1994; Munson et al., 2002). Although all have the theoretic capability and potential to invade and infect the pulp, induce periapical inflammation and bone destruction, only a small proportion of species have been consistently isolated from such root canals (Sundqvist, 1994).

The necrotic root canal system provides a unique ecological niche for bacteria. The lack of oxygen supply, availability of host tissues, and inflammatory exudates produced at the bacteria-inflammatory tissue interface are the primary nutritional factors selecting for bacterial growth (Sundqvist, 1992). Studies have shown that the relative proportion of obligate anaerobes increases, and that of facultative bacteria decreases, with time elapsed after infection (Fabricius et al.,

1982; Tani-Ishii et ai, 1994). Bacteriologic sampling of necrotic root canals of chronically infected teeth with primary apical periodontitis indicate that the microbial population is predominantly anaerobic and Gram-negative

(Bergenholtz, 1974; Sundqvist, 1976). Most of these species have also been identified in periodontal pockets (Moore, 1987; Socransky et al., 1988). The

6 anaerobic infection is usually polymicrobial, typically containing between 2 to 8 species, with no more than 20 species having ever been found in one root canal

(Dahlen and Haapasalo, 1998). Common species that have been isolated in both human and animal studies include Fusobacterium, Streptococcus,

Prevotella, Eubacterium, Peptostreptococcus, Camphylobacter, Porphyromona, and Propionibacterium (Sundqvist, 1994).

Bacterial interactions playa significant role in determining the composition and pathogenicity of the root canal flora. Virtually all microbes that are present in root canals have the potential to initiate a periapical reaction and bone destruction (Sundqvist, 1976). However, some combinations have a tendency to associate together, providing for a mutually supportive (synergistic) environment, whereas others may create negative (antagonistic) associations by competing for nutrients, thus inhibiting the growth of other bacteria (Greiner and Mayrand,

1986; Sundqvist 1992). In studies conducted by Fabricius et al., bacteria originally isolated from the root canals of monkeys with periapically involved teeth were then inoculated in various combinations or as individual strains into the root canals of other monkeys. Infection of root canals with individual bacterial species produced a relatively mild periapical inflammation and little periapical destruction, whereas in combinations, the same bacterial species were highly pathogenic and capable of inducing more severe periapical reactions and larger areas of periapical destruction (Fabricius et a/., 1982b). These observations and later studies have confirmed that the virulence of individual species may vary considerably and highlight the importance of microbial synergy for the

7 pathogenicity of the endodontic flora (Dahlen et al., 1987). The pathogenic

properties of these microorganisms are affected by a variety of factors which

include: (1) the presence in sufficient numbers to initiate and maintain infection,

(2) the ability to acquire nutrients from the host tissue for growth and survival, (3) the ability to evade, withstand, and/or alter host defenses, and (4) the synthesis

and release of a variety of virulence factors including proteolytic enzymes,

metabolites, and cell wall components-such as endotoxin (lipopolysaccharide,

LPS) from Gram-negative bacteria and proteoglycans from Gram-positive

bacteria--into the periapical area where they are capable of damaging host tissues (Horiba et al., 1991; Hashioka et al., 1994). LPS, in particular, is the best

studied of these virulence factors, and has also been identified as a highly potent

initiator of inflammation and a major factor in bone resorption (Dwyer and

Torabinejad, 1981; Dahlen et al., 1981; Schonfeld et al., 1982).

Bacterial Endotoxin-Lipopolysaccharide (LPS)

Structure

Bacterial lipopolysaccharide (LPS) is a fundamental component of the cell

wall of Gram-negative organisms (Figure 1). One bacterial cell contains

approximately 106 LPS molecules, occupying roughly 75% of its outer membrane

(Nikaido, 1996). Although there is a great compositional variation among

lipopolysaccharides derived from different groups of Gram-negative bacteria,

they all have a common basic structure. They are complex glycolipids, consisting

of a hydrophilic heteropolysaccharide and a covalently bound hydrophobic lipid

8 domain known as lipid A (Luderitz et a/. , 1982). The heteropolysaccharide part can be divided into two subdomains, the O-specific polysaccharide chain and the core glycolipid (Figure 2). Lipid A serves as the base structure which secures the

LPS molecule within the bacterial membrane, while the polysaccharide component interacts with the external environment.

o antlgflfl ... - repeat

Hepto } Glucose Ouler LPS G.I.. ~tO$e core Heptose } nnor Kdo eo,..

I lipid A I

Ptotein

Figure 1. General structure of a Gram-negative bacterial cell wall. The inner and outer membrane are separated by a periplasmic space which contains peptidoglycan. Lipopolysaccharide (LPS) is found in the outer membrane and consists of three parts: Lipid A, core glycolipid, and O-specific chain. Kdo forms a covalent bond between the core and lipid A. Image modified from: edoc.hu-berlin.deI.../HTMLlchapter1.html

9 Gram-negative bacterial endotoxin (lipopolysaccharide, LPS) Core glycolipid O-specific polysaccharide chain

O-specific (outer) (inner) oligosaccharide core oligo I~ cch~ride s ubun~

Figure 2. General chemical structure of lipopolysaccharide showing the O-specific chain, core glycolipid (composed of inner and outer regions), and lipid A. Image obtained from: frees pace. virg in.netlr.barclay/edtxsch1.htm

O-specific Chain (O-antigen)

The O-specific chain is a complex polysaccharide composed of one to eight repeating units of identical glycosyl residues. There are enormous structural diversities in O-chains. The length, linkages, and fine structure of the O-chain structure vary from strain to strain, functioning as an important surface antigen, and thus define the serotype specificity of LPS and each bacterial strain containing them (Rietschel et al., 1991). The O-antigen possesses several

intrinsic biological activities and although it's not required for growth in-vitro, its presence is known to help bacteria evade the host immune system and other environmental disturbances (Rietschel et al., 1992). However, not all Gram- negative bacteria possess an O-specifc chain. Such mutants produce rigid, rough-looking colonies when grown on solid agar and are accordingly termed

"rough" (R), whereas wild-type bacterial species containing the O-antigen form colonies with a smooth morphological appearance and are termed "smooth" (S).

10 Core Region

The core region of LPS can be subdivided into an outer and inner region

(Figure 1). Although it is structurally more uniform than the O-chain, some structural variances are found, mainly in the outer core. The outer core region usually consists of common hexose residues such as D-glucose, D-galactose, and N-acetyl-D-glucosarnine. The proximal inner part of the core region is composed of specific a heptose residue, primarily in the L-glycero-D-manno configuration, and 3-deoxy-D-manno-oct-2-ulopyranosonic acid (Kdo) (Holst and

Brade, 1992). Although core regions may vary among bacterial species, the inner core region containing Kdo appears to be well conserved among all Gram­ negative bacteria, as Kdo forms the linkage by which the core is covalently bound to lipid A (Caroff et a/., 2002). It has long been believed that the minimal

LPS structure required for viability of Gram-negative organisms consists of lipid A linked to only two Kdo residues (Raetz, 1990; Schnaitman and Klena, 1993), however viable mutants lacking Kdo and with the basic tetra-acyl form of lipid A, termed lipid IVa, have recently been experimentally produced. These results suggest that lipid IVa may indeed be the actual minimal LPS structural

requirement (Meredith et a/' J 2006). It is unclear what, if any biologic activities the outer core region of LPS is responsible for, however, it is thought that both the inner and outer core contain epitopes that are recognized by host antibodies

(Rietschel et a/' J 1992).

11 Lipid A

Lipid A is a unique and distinctive glucosamine-based phospholipid that anchors LPS to the outer membrane of the gram-negative bacterial cell wall

(Raetz, 1990). It is generally composed of a phosphorylated ~ 1,6-linked 0- glucosamine disaccharide that carries up to six or seven fatty acid chains

(Zahringer et., al 1999). It, along with the Kdo-containil1g inner core region, represents the most structurally conserved region among all Gram-negative species (Figure 3). However, variations can occur in the fine structure, arising from differences in the length, position, and number of the acyl groups.

Kdo;a,lipid A (Re Endotoxin)

14 14 14

14

Figure 3. Structure of Kdo(2)-lipid A found in E.coli, similar to that found in most pathogenic Gram-negative bacteria. Image from: www.lipidlibrary.co.uklLipidsllipidAiindex.htm

It has been demonstrated that lipid A is the region of LPS that is responsible for many of the pathologic effects associated with Gram-negative bacterial infection, since free lipid A has been shown to reproduce the toxic

12 effects of LPS (Galanos et al., 1985). Additional studies have confirmed the role

of lipid A by using chemically synthesized homologues and partial structures that were able to produce identical effects (Kusumoto et al., 1984; Imoto et al., 1987).

This structure, called compound 506, was shown to be identical to E. coli lipid A

purified in a variety of biological assays, and was able to optimally express a full

spectrum of endotoxic activities (Galanos et al., 1985; Kotani 1985). Based on

these findings it was concluded that the cytokine inducing capacity of compound

506 was solely attributed to its three dimensional structure, and that the natural

form of this compound represents the optimal configuration for

immunostimulatory effects.

Host Response

When describing the effects of LPS on the host's tissues, perhaps the

author Lewis Thomas stated it best in The lives of a Cell: "This oppressive

uncontrolled and autodestructive behavior of the host is what makes endotoxin a

venom ...... they are read by our tissues as the worst of news .... when we sense

LPS, we will use all the defenses at our disposal to bomb, block, seal off, and

destroy all tissues in the area" (Thomas, 1974). Since that time, much has been

studied about the structure and basic principles of LPS bioactivity and its

mechanism of action are now well understood (Raetz et al., 1991; Galanos and

Freudenberg, 1993). When Gram-negative bacteria die or multiply, LPS is

liberated and released into the host tissue where it can initiate an inflammatory

response (Rietschel and Brade, 1992a; Barthel et al., 1997) and ultimately result

in periapical bone destruction (Stashenko, 1990; Yamasaki et al., 1992). It has

13 been thought that most, if not all, of the pathogenic effects of LPS are not direct, but rather induced indirectly through its interaction with various host cells. LPS stimulates monocytes, macrophages, and various other host cells to produce and release a large number of pro-inflammatory cytokines such as tumor necrosis factor-a (TNF-a), interleukin (IL)-1, IL-6, IL-8, IL-11, and IL-12 as well as a variety of other small molecules such as lipid mediators, oxygen radicals, and enzymes

(Raetz, 1990; Cohen, 2002). These mediators can then exert either a local or systemic response by acting independently, sequentially, synergistically or antagonistically to induce many of the typical effects of LPS (Rietschel and

Brade, 1992a). In addition to its proinflammatory effects, LPS has been shown to be a potent stimulator of bone resorption by acting on the production and release of cytokines that influence osteoclast differentiation and activation (Ito et al.,

1996; Kikuchi et al., 2001; Jiang et al., 2003). Particularly, LPS has been experimentally shown to stimulate tissue destruction and alveolar bone

resorption in vitro using a mouse osteoblast tissue culture (Pelt et al., 2002) and also in vivo using a rat model (Umezu et al., 1989).

Implication in Endodontic Infections

Numerous studies have reported the presence of LPS in samples taken from the root canals of necrotic teeth (Schein and Schilder, 1975; Schonfeld et al., 1982) and the pulpal-dentinal wall of teeth with apical periodontitis (Horiba et al., 1990). Other studies have confirmed a strong correlation between the levels

of LPS and Gram-negative bacteria found in the infected root canal (Dahlen and

Bergenholtz, 1980). Using a rat model, it was shown that LPS released as a

14 result of death or multiplication of bacteria within the root canal can pass through the apical foramen and into the periapical tissues where they increase in levels from 1 to 70 days after pulp exposure (Yamasaki et al., 1992). The introduction of LPS from F. nucleatum into sterile root canals of teeth in monkeys was shown to induce periapical inflammation and bone resorption (Dahlen et al., 1981).

Similarly, the direct application of S. Minnesota, E. corrodens, and E. coli LPS to the dental pulp also induced significant bone destruction in dogs (Pitts et al.,

1982; Mattison et al., 1987).

Associations have also been found between the LPS content of infected teeth with pulp necroses and clinical endodontic symptoms such as spontaneous pain, tenderness to percussion, and exudation (Horiba et aL, 1991). LPS can contribute to the release of increased levels of vasoactive and neurotransmitter chemicals close to nerve endings in the periapical tissues, resulting in pain

(Seltzer and Farber, 1994).

Calcium hydroxide has been shown to inactivate LPS in in vitro studies by hydrolyzing the highly toxic lipid A component into fatty acids and amino sugars which are non-toxic molecules (Safavi and Nichols 1993, 1994; Barthel et al.,

1997; Olsen et al., 1999). Silva et al. (2002) carried out a study in dogs in which they showed that LPS did not induce the formation of periapical lesions in teeth when combined with calcium hydroxide, confirming the detoxifying role of calcium hydroxide in vivo. The above findings, as a whole, strongly support the connection between LPS and the significant role they play in the pathogenesis of apical periodontitis.

15 Host Recognition of LPS

The molecular mechanism by which host cells recognize bacterial components has been extensively studied and vast breakthroughs have been

made in the identification of molecules in the "LPS receptor complex", which play

a crucial role in recognizing, binding, and mediating the LPS response. The

specific mechanism involved in recognition of LPS by host cells were first

identified in 1990 (Schumann et a/., 1990; Wright et a/., 1990). The basic

mechanism is that LPS is first recognized by, and then forms a complex with, the

soluble LPS-binding protein (LBP). LBP is a lipid transfer molecule that

catalyzes the movement of phospholipids. These LPS/LPB complexes are then

transferred to the membrane bound CD14 receptor, causing a conformational

change, that allows LPS to be transferred to the Toll-like receptor 4 (TLR4) and

myeloid differentiation protein-2 (MD-2) (Hailman et aI., 1994; Tobias et a/.,

1995) (Figure 4). These three proteins-CD14, TLR4, and MO-2 are referred to

as the "LPS receptor complex".

Figure 4. Schematic diagram of the LPS TLR4 LPS receptor complex. LPS is recognized by a LBP complex of three proteins: CD14, TLR4, and ) 4 MD-2. LPS is first bound by LBP which then transfers it to CD 14. CD 14 then presents LPS to TLR4-MD-2. TLR4 is the actual LPS receptor. It LRR CDI 4 is a transmembrane protein characterized by an extracellular domain containing multiple leucine­ rich repeats (LRR) , a transmembrane domain, and an intracellular TlR domain. TLR4 mediates an intracellular signal transduction through three adaptor proteins including MyD88, TlRAP, and Cytoplas TRIF. Image obtained from Fujihara et aI, 2003.

Adaplor proteins

16 The LPS receptor com plex

CD14

CD14 is a 55-kDa glycoprotein that can be found in two forms. The first is a soluble CD14 (sCD14) which can be found in plasma, where they are able to interact directly with the LPS/LPB complex and enable the activation of LPS signaling in cells that lack the membrane-bound CD14, e.g. endothelial cells, fibroblasts, and smooth muscle cells to induce cytokine production (Pugin et al.,

1993; Tapping and Tobias, 1997). The second and more extensively studied form is the membrane CD14 (mCD14), which is embedded in the plasma membrane of myeloid cells via a glycosylphosphatidynositol linkage (Haziot et al., 1988; Wright et al., 1990). It is composed of 10 copies of a leucine-rich repeat (LRR) domain. LRRs are commonly found in various proteins that are involved in substrate recognition and signal transduction (Bell et al., 2003). The binding of LPS to mCD14 on monocytes and macrophages is essential for their activation and can significantly reduce the concentration of LPS required for the stimulation of these cells as compared with LPS alone by 100 to 1000-fold.

Antibodies to CD14 have been shown to significantly inhibit the binding of

LPS/LBP and reduce cytokine production of myeloid cells in response to LPS

(Wright et al., 1990). Additional studies have shown that CD14-knock-out (CD14-

1-) mice are more resistant to LPS-induced lethal shock and produced significantly decreased levels of cytokines when stimulated with LPS (Haziot et al., 1996; Moore et al., 2000). Thus, CD14 was originally identified as a specific receptor for LPS, even though the dependency on CD14 could be partially

17 overcome with higher concentrations of LPS (Perera et al., 2001). However, since CD14 lacks transmembrane and intracellular domains (Figure 4), it cannot by itself initiate a signal transduction in response to LPS, and additional membrane molecules seemed to be necessary for cellular activation. Several biochemical and genetic studies support the theory that CD14 binds LPS, but does not participate directly in signaling (Wright, 1999). Subsequent studies have since shown that TLR4 is the actual signal-transducing receptor for LPS

(Poltorak et aI., 1998). It now appears that the role played by CD14 in LPS signaling is to bind LPS and present it to TLR4 and MD-2. Furthermore, CD14 has been shown to participate in recognition of various bacterial components other than LPS, including Gram-positive cell-wall components such as peptidoglycan (Pug in et al., 1994). CD14 appears able to differentiate between bacterial products and to present them to various TLRs (Muroi et al., 2002).

TLR4

The presence of pattern recognition receptors on immune cells, with the ability to detect and dispose of infectious microbial pathogens without interfering with its own host tissues was put forth to describe the basic concept of innate immunity (Janeway, 1992; Hoffmann et al., 1999). These receptors recognize bacterial products that often share a common molecular pattern and are highly conserved among microorganisms, called the pathogen associated molecular pattern (PAMP), such as LPS in the case of Gram-negative bacteria (Janeway,

1989). It was only in 1996, when a study in Drosophila, which only possess an innate immune system, led to the discovery of the Toll as an essential receptor

18 for host defense against fungal infection (Lemaitre et a/., 1996). To date, at least

10 homologues of Toll, referred to as Toll-like receptors (TLRs) (TLR1-TLR10), have been identified in mammalian species, and 7 of them (TLR 1, TLR 2, TLR3,

TLR4, TLR5, TLR6, and TLR9) have been shown to be required for the recognition and signaling of specific microbial components derived from pathogens including bacteria fungi, protozoa, and viruses (Poltorak et a/., 1998;

Schwandner et a/., 1999; Yoshimura et a/., 1999; Hemmi et a/., 2000; Wyllie et aI., 2000; Alexopoulou et a/., 2001; Hayashi et a/., 2001; Takeuchi et a/., 2001).

The structural hallmark of all known Toll proteins, which represent type I receptors are an extracellular domain containing multiple LRRs, a single transmembrane region, and an intracellular region known as the "TIR" domain which is homologous to the Drosophila Toll and the mammalian IL-1 receptor

(Gay and Keith, 1991) (Figure 4). The distinct responses to specific microbial products are a result of minor variances in the extra- and intracellular domains of

TLRs.

The first human TLR to be identified was TLR4, and is predominantly found on immune cells such as macrophages and dendritic cells. There is now compelling evidence that TLR4 is in fact an essential signal-transducing receptor for LPS (Medzhitov et a/., 1997). The establishment of a link between TLR4 and

LPS recognition came through the use of positional cloning studies of the Lps locus in C3H/HeJ and C57BLl10ScCr mice which are both insensitive to LPS.

The Lps locus contains the Tlr4 gene and both of these mice were shown to have mutations in this region. C3H/HeJ mice were shown to have a single point

19 mutation in the TIR domain of Tlr4 which causes proline to be replaced with

histidine at position 712 of the polypeptide chain, whereas C57BLl10ScCr mice were shown to have a null mutation, resulting in total deletion of the Tlr4 gene

(Poltorak et al., 1998; Qureshi et al., 1999). The essential role of TLR4 for LPS signaling was further confirmed when mice rendered deficient in the Tlr4 gene

(TLR4 knockout mice) where shown to be as insensitive to LPS as C3H/HeJ

mice (Hoshino et al., 1999). TLR4 mutations are also associated with a decreased response to LPS in humans (Arbour et al., 2000). Conversely, transfection of TLR4 in human embryonic kidney cells that were unresponsive to

LPS was shown to restore the LPS response (Chow et al., 1999).

TLR4, however, is not only exclusively involved in enterobacterial LPS

signal transduction. It is also implicated in the recognition of several other

endogenous and exogenous ligands. These include heat-sensitive cell­

associated factor derived from Mycobacterium tuberculosis (Means et al., 1999),

Taxol, which is a diterpene purified from the bark of the Western yew (Taxus

brevifolt) (Kawasaki et al., 2000), heat shock protein 60 (Vabulas et al., 2001),

fusion (F) protein of respiratory syncytial virus (Kurt-Jones et al., 2000), as well

as oligosaccharides of hyaluronic acid, heparin sulfate, and fibrinogen (Takeda et

al., 2003).

Ambiguous Role of TLR2

There is a general consensus that TLR2 is involved in the recognition of

components from a variety of microorganisms. These include Gram-positive,

mycobacterial, and fungal compounds such as peptidoglycan, lipoteichoic acid,

20 various lipopeptides, and lipoarabinomannan (Lien et a/., 1999). However, TLR2 was also originally believed to be the long sought after LPS receptor. This was

based on several transfection studies that showed that expression of the

mammalian TLR2 in human embryonic kidney cells that were LPS-unresponsive were now capable of responding to LPS (Kirschning et a/., 1998; Yang et aI.,

1998). However, later studies revealed that overexpression of TLR2 causes cell

lines to become exceedingly sensitive to trace amounts of non-LPS lipopeptide

contaminants that may have been present in the LPS preparations (Heine et a/.,

1999; Takeuchi et a/., 1999; Faure et a/., 2000). Repurification of LPS

preparations of Sa/monella and E. coli clearly demonstrated that cells are

activated through TLR4 as the principal signal-transducing molecule, and not

TLR2 (Hirschfeld et a/., 2000; Tapping et a/., 2000). Furthermore, similar types

of LPS elicited the same response in TLR2 knockout mice as in wild-type mice

(Takeuchi et a/., 1999).

Adding to the complexity of LPS signaling, it now appears that the

chemical structure of LPS itself may be an important factor in its recognition by

different receptor clusters, resulting in different cellular responses (Hirschfeld et

a/., 2001; Werts et a/., 2001). Historically, most of the reported studies have

been performed using commercially available preparations of LPS of E. coli or

Sa/monella. However, recent publications indicate that not all LPS chemotypes

induce signal transduction through TLR4, specifically LPS of Leptospira

in terrogans, Porphyromonas gingiva/is, and Neisseria meningitidis have been

shown to signal via TLR2 (Werts et a/., 2001; Bainbridge and Darveau, 2001;

21 Pridmore et al., 2001). A recent study suggests that the lipid A segment of these bacterial species may exhibit several chemical modifications, specifically in the number of acyl chains, which alters the shape of the LPS molecule, distinguishing them from the typical LPS of Gram-negative bacteria (Netea et al.,

2002). Thus, TLR2 may recognize distinct epitopes within lipid A of L. interrogans, P. gingivalis, and N. Meningitidis, in addition to other structurally unrelated components from Gram-positive bacteria.

Although TLRs are believed to be the main receptors involved in LPS signal transduction, new experiments have identified an additional heterogenous complex of four proteins that may be involved in LPS recognition and signal activation. Using antibodies against Hsp70, Hsp90, CXCR4, and GOF-5, researchers were able to inhibit LPS-induced TNF-a production and activation of monocytes (Triantafilou et al. 2001; Triantafilou et a/. 2001 a). Thus, it appears probable that there are a host of several membrane proteins that form an LPS receptor domain.

MD-2

1\110-2 is a small secreted glycoprotein that lacks a transmembrane domain, which acts as an extracellular adaptor protein in conjunction with TLR4, and is essential for LPS signaling to occur (Shimazu et al., 1999) (Figure 4). The physiologic necessity for MO-2 in the LPS response has been demonstrated using a mutant form of mice which lack MO-2 (Nagai et al., 2002). Bone marrow­ derived macrophages from mice lacking MO-2 were unable to produce inflammatory cytokines upon stimulation by LPS. These findings were reinforced

22 in a study using a mutant cell line derived from Chinese hamster fibroblasts in which there was normal cell surface expression of TLR4, but also a point mutation in a conserved region of MD-2 (C95Y) that showed no response to LPS.

Additionally, in another study, wild-type MD-2 was able to restore the LPS response in cells expressing TLR4 but lacking MD-2 (Schromm et al., 2001;

Visintin et al., 2001).

It has also been demonstrated that MD-2 is involved in regulating the intracellular positioning of TLR4 (Nagai et aI., 2002). In embryonic fibroblasts lacking MD-2, TLR4 predominantly accumulated within the Golgi apparatus and failed to be correctly transported to the cell surface.

Thus it appears that MD-2 plays a pivotal role, having both a regulatory activity for the cellular distribution of TLR4, and also involved in LPS recognition and signal transduction through TLR4. In fact, LPS binds to MD-2, which then associates with TLR4 by means of the extracellular LRRs, inducing NF-KB activation and signaling via TLR4 (Visintin et al., 2003). It therefore seems plausible that the functional integrity of the "LPS Receptor Complex" depends on the cell surface expression of a variety of host proteins and the concept of a

"monogamous" relationship between LPS and TLR4 may in reality be an oversimplification.

LPS Signaling through TLR4

My088-0ependent Signaling Pathway

Since the TLRs share sequence homology with the IL-1 receptor family,

LPS sjgnaling is thought to occur in a similar manner. These two pathways, are

23 in fact, mediated by common components. The principle signaling pathway activated by TLR4 in response to LPS occurs through sequential recruitment of adapter proteins. These adapters include myeloid differentiation factor 88

(MyD88), a family of IL-1 receptor-associated kinases (IRAK), and TNF receptor- activated factor 6 (TRAF6) (Muzio et al., 1996; Burns et al., 1998; Medzhitov et al., 1998). The cytoplasmic adapter MyD88, which is also a Toll-like molecule, is normally bound to the intracellular "TIR" domain of TLR4 by TolllToll interactions.

Upon stimulation, MyD88 recruits IRAK-4 to the receptor complex which then facilitates the phosphorylation of IRAK-1. Activated IRAK-1 subsequently dissociates from the receptor complex and interacts with TRAF6, which results in the activation of two distinct signaling pathways, NF-KB or c-jun N-terminal kinase (JNK), both of which are involved in the activation of numerous inflammatory genes and expression of inflammatory cytokines (Figure 5) (Cao et al. , 1996; Muzio et al., 1997; Burns et aI., 1998; Medzhitov et al., 1998. Muzio et al.,1998). Additionally, gene targeting studies have shown that NF-KB has a critical role in osteoclast differentiation (Franzoso et aI., 1997; lotsova et aI.,

1997).

Figure 5. Schematic diagram of the My088- dependent and My088-independent pathways. Refer to text for explanations. Image obtained from : www.rsc.org/delivery/ ArticleLinking/Display H ...

24 My088-lndependent Signaling Pathway

Although MyD88 is an absolute requirement for the production of inflammatory cytokines, MyD88-deficient macrophages showed a delayed activation of the NF-KB and JNK pathways in response to LPS stimulation compared with macrophages from wild-type mice (Kawai et al., 1999). This indicates that even though LPS-induced inflammatory cytokine production is entirely dependent on the MyD88 pathway, there also exists a MyD88- independent component in LPS-TLR4 signaling.

LPS stimulation of MyD88-deficient macrophages leads to activation of the transcription factor IFN-regulatory factor 3 (IRF-3), which subsequently induces

IFN-~. IFN-~ then activates Stat1, which results in the expression of several IFN­ inducible genes (Figure 5) (Kawai et al., 2001; Doyle et al., 2002; Toshchakov et al., 2002).

Regulation of Osteoclast Formation

Osteoclasts are large, multinucleated specialized giant cells responsible for bone resorption that arise from a hematopoietic stem cell lineage of monocytes and macrophages (Suda et al., 1992). Osteoclastic bone resorption consists of multiple steps and studies have identified several key elements thought to be important for osteoclast differentiation (osteoclastogenesis) and activation (Teitelbaum and Ross, 2003). These include macrophage-colony stimulating factor (M-CSF), receptor activator of nuclear factor kappa B ligand

(RANKL), tumor necrosis factor-a (TNF-a), interferons (IFNs), and interleukins

(I Ls). Of these factors, M-CSF and RANKL are thought to play an essential role

25 proliferation Mononuclear Osteoclast & osteoclast

Osteoblasts/Stromal Cells The in vivo significance of the RANKL-RANK signaling pathway in regulating skeletal development and bone remodeling has been demonstrated by a series of gene disruption studies using a mouse model (Teitelbaum and Ross,

2003). Mice lacking either RANKL or RANK developed severe osteopetrosis, with total occlusion of the bone marrow space within endosteal bone, due to failure to form osteoclasts (Dougall et al.. 1999; Kong et al., 1999). Conversely, the targeted disruption of OPG led to the development of early onset osteoporosis due to increased numbers of activated osteoclasts (Bucay et al.,

1998).

RANK Signaling in Osteoclast Differentiation

RANK signaling is mediated through specific adapter molecules called

TNFR-associated factors (TRAFs) (Rho et al., 2004). Although the TRAF family contains six members (TRAFs 1, 2, 3, 4. 5. and 6), and RANK can directly interact with five of them (TRAFs 1. 2, 3, 5, and 6), only TRAF-6 appears to be critical for osteoclast differentiation (Galibert et al., 1998; Darnay et a/., 1999).

RANKL stimulation facilitates the recruitment of TRAF6 to one or more of the three binding motifs in the cytoplasmic domain of the RANK receptor which then activates several downstream signaling cascades. Six key signaling pathways have been identified in osteoclasts: nuclear factor of activated T-cell (NFAT) c1. nuclear factor kappa B (NF-kB), Aktlprotein kinase B (PKB). Jun N-terminal kinase (JNK), extracellular signal-regulated kinase (ERK) and p38. all of which promote survival and differentiation (Figure 7) (Boyle et a/., 2003).

27 IC Oom

?

Akc FATc1 ! ! Osteoclast Differentiation Figure 7. Schematic representation of RANK signaling in osteoclast differentiation. Modified from Feng , 2005.

However, recent findings support the notion that LPS and some

inflammatory cytokines such as TNF-a and IL-1 may also be directly involved in

osteoclast differentiation and activation through a mechanism partially

independent from that of the RANKL-RANK interaction (Jimi et ai, 1999; Suda et

al., 2002; Kobayashi et al., 2000; Jiang et al., 2006). The intracellular signaling

cascade of TLR4 is similar to that of IL-1 receptors and both of these receptors

have been shown to use TRAF6 as a common signaling adapter molecule

(Kobayashi et al., 2004). When osteoclast precursors were stimulated with both

LPS and RANKL, LPS-induced osteoclast formation was observed even in the

presence of OPG and IL-1 receptor antagonists (Suda et al., 2002; Jiang et al.,

2006). Osteoclast formation was also stimulated by LPS in preosteoclast cells from mice missing tumor necrosis factor (TNF)-receptor-I or TNF-receptor-II

(Suda et al., 2002). These results suggest that LPS stimulates osteoclast

28 formation independent of RANKL, IL-1, or TNF-alpha action, and have opened new areas for exploring the molecular mechanisms of osteoclast differentiation.

They also constitute a potential therapeutic target for the modulation of excessive osteoclast differentiation in pathogenic bone and oral diseases (Figure 8).

TNF-a RANKL IL-1 LPS /\ l

TLR4

I NF-KB, JNK, NFATc1, etc. I

r;\ _~__ ~. ~••• ~NF"'B' JNK, ~FAT'" .':- I@.:••• V Differentiation Activation Activated Osteoclast t Quiescent Osteoclast precursor M-CSF Osteoclast

Figure 8. Schematic representation of osteoclast activation by RANKL, IL-l, and LPS through their respective receptors. TRAF6 appears to act as a common signaling adapter molecule involved in all three pathways. Modified from Katagiri and Takahashi 2002.

NFATc1

NFATc1 is the most strongly induced transcription factor gene mediated by RANKL stimulation. It has also been shown to be a key regulator of osteoclastogenesis and plays a critical role in the terminal differentiation of osteoclasts (Takayanagi et al., 2002). RANKL-induced recruitment of TRAF6 results in the induction of intracellular calcium, which leads to the activation of calcineurin (Takayanagi et al., 2002). Activated calcineurin then

29 dephosphorylates and activates NFAT1, allowing it to translocate to the nucleus to form a ternary complex with c-Fos and c-Jun to stimulate NFATc1 gene expression (Figure 7) (Ikeda et al., 2004). At the final stage of osteoclast differentiation, NFATc1 works in conjunction with Fos and Jun proteins to stimulate osteoclast-specific genes such as tartrate-resistant acid phosphatase

(TRAP), calcitonin receptor, and cathepsin K (Ikeda et al., 2004). Thus it appears that the NFATc1 pathway is a crucial component of osteoclast differentiation, and inhibition of this pathway may provide yet another potential therapeutic approach for the treatment of bone diseases.

RNA Interference (RNAi)

RNA interference (RNAi) is a process in which specific sequences of small pieces of double-stranded RNA (small interfering RNA [siRNA]) are used to silence the expression level of sequence-homologous genes (Dykxhoorn and

Lieberman, 2005). It now appears that it is an evolutionary conserved process in plants and invertebrates that may have originated as a cellular defense, whose natural function is to protect cells against viral infection and other potentially harmful genetic elements that make double-stranded RNA (dsRNA) intermediates (Lee and Ambros, 2001).

RNAi is arguably one of the most significant and promising technological advances in modern scientific history. Science magazine hailed it as the

"Breakthrough of the Year" in 2002, and in 2006 the Nobel Prize in Physiology or

Medicine was awarded to those responsible for its discovery. This phenomenon

30 was first discovered in plants when researchers were trying to genetically

engineer a more intensely colored petunia using a transcribed sense transgene

that encoded an enzyme for the synthesis of purple pigment, but unexpectedly

found suppression of the homologous endogenous gene (Napoli et al., 1990).

This was termed post-transcriptional gene silencing (PTGS). However, it was

Andrew Fire, Craig Mello, and colleagues who made the discovery that

sequence-specific dsRNA was the source of gene silencing in the nematode worm-Caenorhabditis elegans-and termed this RNA interference (Fire et al.,

1998). In their experiment, they separately introduced sense and antisense RNA

to a particular gene into the cells of the worm and found, at best, the antisense

RNA caused a modest reduction in gene expression. Yet, when both molecules

were allowed to hybridize and then injected, there was a profound and specific

interference.

Additional studies revealed that when long dsRNA molecules are

introduced in plants and invertebrates, they are internally processed by an

enzyme called Dicer into small dsRNAs, 21 to 23 nucleotides (nt) in length,

referred to as siRNA (Hammond et al., 2000, Zamore et al., 2000; Bernstein et

al., 2001). However, in mammals, exposure to dsRNAs greater than 30 base

pairs provokes a systemic and nonspecific inhibition of mRNA translation as a

result of activation of the antiviral interferon response (McManus and Sharp,

2002). It was thus a significant breakthrough when, in 2001, it was demonstrated

that chemically synthesized short dsRNA molecules of 21-22 nt in length­

siRNA-could be used to directly trigger RNAi in mammalian cells without

31 initiating the interferon response (Elbashir et al., 2001). Since then, RNAi has revolutionized biological research as a new and powerful tool for the study gene function by suppressing its expression, and attracted the attention of academic researchers, the medical community, and the pharmaceutical industry for its potential therapeutic applications in the treatment of disease.

Mechanism of RNA Interference

RNAi is triggered when the host cell encounters long dsRNAs produced by viral sources or exogenously administered synthetic siRNA precursors (Lee and

Ambros, 2001). Once in the cytoplasm, these RNA molecules are processed by the ribonuclease III-like enzyme known as Dicer, to generate RNA duplexes 21-

22 nt in length (siRNA) with a 2- to 3-nucleotide unpaired overhang at each end

(Elbashir et al., 2001 a). These siRNA fragments are then incorporated into large protein complex, known as the RNA-induced silencing complex (RiSe), by which the double-stranded siRNA is unwound into single-stranded siRNA (Nykanen et al., 2001). The antisense strand of the duplex siRNA then guides the RiSe complex to the homologous mRNA. Once bound to its target through simple

Watson and erick base paring, RiSe is activated by ATP and cleaves the mRNA at a single site approximately in the middle of the region paired with the antisense siRNA, resulting in silencing of the target gene (Elbashir et al., 2001a;

Martinez et al' J 2002). The cleavage products are degraded and released from the siRNA-RiSe complex, freeing it to search for and further diminish the available pool of target mRNA (Figure 9) (Meister and Tuschl, 2004).

32 Dicer MECHANISM LongdsRNA Dicing...

siRNA

IFN response RIse & non specifIC complex gel'l! silencing

Nucleus

f J' Sequence speciiIC gene silencing

Figure 9. Schematic representation of the RNAi mechanism. RNAi is induced when the host cell encounters long dsRNA from viruses or exogenously administered synthetic siRNA. Once in the cytoplasm, they undergo processing by an enzyme called Dicer. This results in the formation of a dsRNA between 21-23 nucleotides in length. This siRNA binds with several cellular proteins forming a complex referred to as RNA interfering silencing complex (RISe), which guides the siRNA to its homologous target mRNA. Once bound to its target through simple Watson and erick base paring, RISe then cleaves the mRNA approximately in the middle of the region paired with the antisense siRNA, and effectively leads to further degradation of the mRNA. Image obtained from : http://arunbt.googlepages.com/

Design of Effective siRNA probes

Functional RNAi is dependent upon the sequence specificity of the siRNA probe to the target gene of interest. Thus, design of the siRNA sequence is crucial for effective gene silencing. Currently, siRNA design is based on an understanding of RNAi biochemistry, and several groups have developed empirical guidelines for effective siRNAs design. These guidelines recommend

33 the use of siRNAs that are 21 nt long with a 3' overhang of 2 nucleotides. The siRNA should be complimentary to the target mRNA at a location 75-100 bases downstream of the start codon of the gene of interest and the target site should have a GC content less than 50 percent. Finally, a BLAST-search of the target site should be carried out to the appropriate genome database to ensure that only one gene is being targeted and 3-4 siRNA should be tested for each gene to minimize possible nonspecific off-target effects (Elbashir et al. 2001 b, Khvorova et al., 2003; Reynolds et al., 2004). At this time, the siRNAs of many gene products of interest have been synthesized and act as readymade Dicer products.

Delivery Strategies of siRNA

The delivery of nucleic acids into mammalian cells is called transfection.

Functional RNAi requires effective transfection procedures without side-effects or cytotoxicity. Successful introduction of siRNA into cells of interest have been demonstrated using either plasmid or viral vectors (Brummelkamp et al., 2002;

Paddison et al., 2002). Synthetic siRNAs delivered to cells in culture by electroporation or the use of lipophilic agents have also been used to successfully silence target gene expression (Elbashir et al., 2002; Mellitzer et al.,

2002). There are several commercially available transfection kits that can be used for the application of RNAi. Lipofectamine 2000 and Oligofectamine

(Invitrogen) are two that are routinely used for siRNA delivery.

34 Therapeutic Potential of RNAi

Given that most diseases are genetic-based and the genetic etiology of many disorders has been defined, the therapeutic promises of RNAi are potentially enormous. It seems evident that RNAi is not only a powerful research tool for studying gene function, but that it is also a fast and inexpensive method to selectively silence a gene product in complex biological systems. The sequence-specific gene inhibition by siRNA has shown genuine therapeutic potential and opened new horizons in the areas of cancer research, HIV treatment, genetic disorders, and pharmaceutical drug development (Jacque et al., 2002; Brummelkamp et al., 2003; Dorsett and Tuschl, 2004; Whelan, 2005).

35 Aim of Study

Thus the objective of this study was to utilize RNAi using specific siRNA to silence TLR4 or NFATc1 expression in monocytes and osteoclast cells in order to modulate the effects of LPS stimulation, and to provide a potential therapeutic approach in the field of endodontic research. The specific aims for this study are:

Specific Aim 1: To examine the efficiency of siRNA transfection in

monocytes and osteoclasts.

Specific Aim 2: To examine the expression of TLR4 and NFATc1 levels in

osteoclast cells transfected with specific siRNA

Specific Aim 3: To examine the biological effect of the suppression of

TLR4 and NFATc1 with effective siRNA. The transfected and control cells

will be stimulated with LPS. The production of cytokines will be examined

with ELISA and osteoclast formation will be quantitatively analyzed.

36 Material and Methods

Preparation of Osteoclasts

Osteoclast-like cells (OCl) were differentiated from RAW 264.7 cells, a mouse hematopoietic cell line (American Type Culture collection, Rockville, MD).

For morphological examination, RAW 264.7 cells were plated at a density of

40,000 cells/well in 24 well plates in alpha modified Eagle medium with 10% fetal bovine serum (Invitrogen, Carlsbad, California). The cells were incubated at

37°C in a humidified atmosphere containing 5% CO 2.

TRAP Assay

Tartrate resistant acid phosphatase (TRAP) is a marker enzyme specific for osteoclasts. At 96 h of culture, cells were fixed with 2% paraformaldehyde, washed with phosphate buffered saline, and treated for 20 minutes with 0.2%

Triton X-100 solution to permeabilize cell membranes. Cytochemical staining of tartrate-resistant acid phosphatase (TRAP)-positive cells was performed as described previously (Holliday et a/., 2003). TRAP-positive cells appeared dark red. Only TRAP-positive cells with more than 3 nuclei were counted. The values are expressed as means ± SE of triplicate cultures.

37 RNA Extraction, Quantification, and Reverse Transcription

Total RNA was extracted using TRIZOL reagent (Invitrogen) and phenol/choloroform according to manufacturer's instructions. RNA was dissolved in Tris-EDTA (TE), PH 7.4 and the concentration of RNA was determined by measuring the spectrophotometric absorbance at 260 nm. The concentration of extracted RNA was 0.5 I-Ig/I-II-1 I-Ig/I-II. RNA was treated with DNAse I (Invitrogen) for 15 minutes followed by DNase I inactivation with 25 mM EDTA at 65°C to remove genomic DNA contamination. Reverse transcription was carried out in a

20 1-11 volume containing about 3 I-Ig of RNA, 11-11 of 50 ng/I-II random hexamers and 1 IJI annealing buffer, 10 1-11 2X first-strand reaction mix and 2 1-11 superscript

III/RNase OUT enzyme mix (Invitrogen) at 25°C for 10 minutes and then at 50°C for 50 minutes.

Real-time peR

Taqman real-time PCR was performed from 1 1-11 of cDNA using TaqMan

Universal PCR Master Mix (Applied Biosystems, Foster City, CA) with 100-nM

primers and a 50-nM probe. The Taqman Real-time RT-PCR was performed on a Taqman ABI 7500 sequence Detection System (Applied Biosystems).

Unlabeled specific primers and the TaqMan MGB probes (6-FAM dye-labeled) for detecting the mouse TRAP gene (Assay 10: Mm00475698 m1); calcitonin

receptor gene (Assay 10: Mm00432271 m1) and cathepsin K gene (Assay 10:

Mm00484036 m1) were used. A Taqman eukaryotic 18S endogenous control kit was used for housekeeping gene control. Cycling conditions were: After an initial

38 hold of 2 minutes at 50°C and 10 minutes at 95°C, the samples were cycled 40 times at 95°C for 15 seconds and 60°C for 1 minute. Each sample was assayed in triplicate.

Traditional PCR used to analyze the amount of PCR product at the end of the reaction does not truly represent the initial amount of starting material whereas real-time PCR monitors the amount of amplicon in the reaction as it is produced during each PCR cycle. As a result, real-time PCR methodology provides fast, precise, and accurate results by monitoring the amplification of products during the reaction and allows quantification of rare transcripts and small changes in gene expression. The Taqman technique is most widely used for real-time PCR detection techniques. It uses the 5'-3' exonuclease activity of

Taq DNA polymerase to cleave a dual-labeled probe annealed to the target sequence during PCR amplification. The probe, a sequence complementary to the mRNA located between the forward and reverse primers, contains both a fluorescent reporter dye at the 5'-end and a quencher dye at the 3'-end. The fluorescent emission activity of the reporter dye is neutralized by a quenching dye when the TaqMan probe is hybridized to its target sequence. During PCR amplification, Taq DNA polymerase cleaves the TaqMan probe into fragments through its 5'-3' endonucleolytic activity. Thus the reporter dye is separated from the quenching dye, resulting in an increase in fluorescence that is directly proportional to the amplification of the molecule. Applied Biosystem has commercially available fluorescence-labeled primers and probes for mouse osteoclast-specific genes and endogenous control gene 185 ribosomal RNA.

39 Real-time PCR is currently considered the gold standard for quantitative measurement of mRNA, having both high sensitivity and specificity.

Statistical Analysis of Ct Comparative Gene Expression

The comparative Ct method was applied to determine comparative expression levels between samples relative to control gene expression. To examine regulation by NFATc1-specific or TLR4-specific siRNA, the amplification threshold cycle value (Ct) from each treated sample was subtracted from the control-treated sample cycle values (ACt=Ct control-Ct treated). The ratio was obtained by calculating the values obtained for gene of interest and the house­ keeping gene 18S rRNA. The fold change of the test gene was determined as

2(L'lCI gene- L'I ct 185).

Data are expressed as mean values ± SEM. Statistical significance of differences was determined by one way ANOVA and followed by posthoc test

(Fisher's protected least significant difference (PLSD). Differences were considered statistically significant at P < 0.05.

40 siRNA Transfection

TLR4 or NFATc1 were silenced by using TLR4 or NFATc1 SMARTPOOL small interfering RNA (siRNA) reagent (Dharm), respectively.

For osteoclast examination, RANKL-stimulated RAW 264.7 cells on glass coverslips in 24-well plates for first 24 h were either not transfected or transfected using 1.5 U control or effective siRNA and 1.5 U fluorescent double-stranded

RNA (Dharham) combined with 2 1-11 lipofectamine 2000 (Invitrogen) in Opti-MEM media supplemented. Six hours after transfection, the media was replaced by aMEM with fetal bovine serum (FBS) and 100 ng/ml LPS. No antibiotics were used. The cells were incubated for 30 h at 3rC in a CO 2 incubator for additional

4 days after which they were fixed in 2% paraformaldehyde. The nuclei were then counterstained with a DAPI stain, which binds the nucleotides, in order to visualize the relative location of the siRNA. Only cells with uptake of the fluorescent oligomer (FITC) by fluorescent microscopy were identified as having the control siRNA.

For assessment of cytokine expression, RAW264.7 cells were plated on

24-well plates with DMEM and 10% FCS at density 40,000/well for 24 h. Cells were then either not transfected or transfected using 1.5 U control or experimental siRNA and 1.5 U fluorescent oligomer combined with 2 1-11 lipofectamine 2000. Six hours after transfection, the media was replaced by

DMEM with FBS. The cells were incubated at 3rC in a CO2 incubator for an additional 3 days. During the last 24 h of culture, cells were stimulated with 100

41 ng/ml LPS. The medium were collected and stored in -70°C for ELISA analysis.

RNA was extracted for real-time PCR assay.

ELISA

Concentrations of IL-1, IL-6, and TNFa in culture supernatants were determined by ELISA in triplicate with commercial ELISA Duo systems (R&D systems), according to the respective manufacturer's instructions. For each sample and assay, the mean of the triplicate measurement were calculated.

Immunostaining and Microscopy

Marrow osteoclasts or RAW 264.7-derived osteoclast-like cells were fixed

in 2% formaldehyde in PBS on ice for 20 minutes. Osteoclasts were detergent­

permeabilized with 0.2% Triton X-100 in PBS for 10 minutes, washed, and

blocked in PBS with 2% bovine serum albumin (BSA) for 2 h. The cells were stained with rhodamine-phalloidin or antibodies recognizing TLR4, NFATc1 at a dilution of 1: 100 in PBS. Secondary antibodies were diluted according to the

manufacturer's instructions.

42 Results

Evaluation of siRNA Transfection in Monocytes

Traditionally, it is difficult to manipulate gene expression in monocytes and especially osteoclasts, because they are terminally differentiated cells. Monocyte cells were transfected with a fluorescently labeled control siRNA using a commercially available lipfectamine kit and visualized by fluorescence microscopy 72 hours post transfection (Figure 9). The nuclei were counterstained with a DAPI stain, which binds the nucleotides in order to visualize the relative location of the siRNA (Figure 10).

Figure 9. Monocytes transfected with Figure 10. Monocyte nuclei stained with control fluorescent-labeled siRNA and DAPI. visualized by fluorescence microscopy.

When the two images above are superimposed, we see the red dots around the nuclei, which indicates that the siRNA are delivered into the cytoplasm with high efficency (Figure 11).

43 Figure 11. SiRNA are delivered mainly to the cytoplasm with high efficency.

Evaluation of siRNA Transfection in Osteoclast-like cells

Similarly, we used osteoclast-like cells that were differentiated using LPS or RANKL and tranfected them with fluorescent-labeled siRNA (Figure 12) and the nuclei were stained with DAPI (Figure 13).

Figure 12. Osteoclast-like cells Figure 13. Osteoclast nuclei stained with transfected with fluorescent-labeled DAPI. siRNA.

44 When the two images above are superimposed, we see that osteoclasts are multinucleated (as indicated by the blue dots) and the fluorescent-labeled siRNA are highly concentrated in the peripheral cytoplasm around the nucleus.

,.• • . iI " f. .. • ~ , . ~\O -" e t', . f ' ", "., .<. , p . 1I .. .•• , ".. "'- .- . IQ' ..., t .... •... ~ ~ Q ~ - ,t. "' .~ ... '. ,, \;. .. . •• ...

Figure 14. SiRNA are delivered mainly to the cytoplasm of osteoclasts with high efficiency.

When we stained with TRAP, which is a purple stain and marker for osteoclast identification, we see TRAP+ cells that are phenotypically identical to untransfected osteoclasts (Figure 15).

Figure 15. Osteoclasts transfected with siRNA appear phenotypically identical to untransfected osteoclasts.

45 Silencing NFATc1 Expression in Osteoclasts with siRNA

In the next step, we examined the efficacy of siRNA in silencing NFATc1 protein expression. In the control group, osteoclast cells were transfected with control siRNA and immunocytologically stained with anti-NFATc1 antibody. This method locates NFATc1 protein expression inside the cell. We observed intense nuclear accumulation of NFATc1 protein in osteoclasts which was to be expected, as NFATc1 is a transcription factor and therefore should be located in the nucleus (Figure 16). In the experimental group, osteoclasts were transfected with NFATc1-specific siRNA and similarly stained witl, anti-NFATc1 antibody.

We observed a significant reduction of NFATc1 protein expression in the nucleus as compared to the control (Figure 17).

Figure 16. Osteoclasts transfected with Figure 17. Osteoclasts transfected with control siRNA show intense nuclear NFATc1 show a significant reduction of accumulation of NFATc1 protein (arrows). NFA Tc1 protein in the nucleus (arrows).

46 When the nuclei were counterstained with DAPI and the images were superimposed, we can better appreciate that the nuclei are still present in both groups, even though there was reduced NFATc1 protein expression in the experimental group (Figure 18).

.~

•• .' --""'. ". • ~ I { , e '( t • e • \. "I .,-.. e- " • . ~ --.' . ~ . ".. ~ ~ . - .•... .• ..v " :., .. .. ·--:'-:1 -, ,.. " / . •• I ' •

Control siRNA NFATc1 siRNA Figure 18. Nuclear staining with DAPI reveals that nuclei are still present in both the control and experimental groups.

This indicates that we were able to partially silence the expression of NFAT c1 in osteoclasts using NFATc1-specific siRNA.

Silencing TLR4 Expression in Osteoclasts with siRNA

Similarly, we examined the efficacy of siRNA in silencing TLR4 protein expression. In the control group, osteoclast cells were transfected with control siRNA and immunocytologically stained with anti-TLR4 antibody (Figure 19). In the experimental group, osteoclasts were transfected with TLR4-specific siRNA and also stained with anti-TLR4 antibody. We observed a significant reduction in

TLR4 expression on the cell surface as compared to the control (Figure 20).

47 Figure 19. Osteoclasts transfected with Figure 20. Osteoclasts transfected with control siRNA and stained with Anti­ TLR4-specific siRNA and stained with TLR4 antibody. Anti-TLR4 antibody.

When the nuclei were counterstained with DAPI and the two images superimposed, we can see that the nuclei are unaffected in both groups, even though there is reduced TLR4 protein expression in the experimental group

(Figure 21).

Control siRNA TLR4siRNA Figure 21. Nuclear staining with DAPI reveals that nuclei are still present in both the control and experimental groups.

This indicates that we were also able to partially silence the expression of TLR4 in osteoclasts using TLR4 specific siRNA.

48 Biological Effects of Silencing NFATc1 or TLR4 Expression in Monocytes

Since monocytes are the predominant producers of cytokines in response to LPS stimulation, we then examined what effect silencing NFATc1 or TLR4 expression would have on TNF-a, IL-6, and IL-1 production. Monocytes were transfected with either N FAT c1-specific, TLR4-specific, or control siRNA and the cells were stimulated with LPS. Media was collected after 24 hours and analyzed for cytokine production using ELISA. Results are shown in Table 1.

Analysis of Variance revealed cells in both the NFATc1-specific and TLR4- specific siRNA groups showed a statistically significant resistance to LPS stimulation as indicated by the down regulated TNF-a and IL-6 levels compared with that in the control siRNA group (p

Monocyte Cytokine Production

IL-6 ELISA (measured in ng/ml) NOLPS LPS+control siRNA LPS + TLR4 siRNA LPS +NFATc1 siRNA Not detectable 9.52 +/-2.05 *3.48 +/-0.78 *5.11 +/-0.98

TNF-alpha ELISA (measured in ng/ml) Not detecatble 23.49 +1-0.98 *15.17 +/-1.01 *18.31 +/-1.43

IL-1 alpha ELISA (measured in pg/ml) Not detectable 30.7 +/-3.2 25.7 +/-3.8 32.7 +/-2.5

Table 1. Biological effects of silencing NFATc1 or TLR4 on monocyte cytokine production *denotes statistical Significance relative to control, P

49 Monocyte Cytokine Production

30 .------. 25 20 IL-6 15 DTNF-alpha 10 5 o LPS+lLR4 LPS + NFATc1 siRNA siRNA Treatment Groups

Figure 22. Inhibition of cytokine release in monocytes mediated by siRNA. * denotes statistical significance relative to control, P

Biological Effects of Silencing NFATc1 or TLR4 Expression on Osteoclast

Formation

Monocytes were stimulated with RANKL for 24 hours and then transfected with either NFATc1-specific, TLR4-specific, or control siRNA. Cells were then stimulated with LPS for an additional 72 hours. TRAP+ cells with more than three nuclei were counted. Results are shown in Table 2.

Number of Osteoclasts Formed

IControl siRNA I TLR4 siRNA I NFATc1 siRNA I I 356 +/-25 I *234 +/-58 I *152 +/-39 I

Table 2. Biological effects of silencing NFA Tc1 or TLR4 on osteoclast formation. *denotes statistical significance relative to control, P

50 Analysis of Variance revealed a statistically significant fewer number of osteoclasts formed in cultures treated with NFATc1 or TLR4-specific siRNA as compared with that in the control siRNA group (P

There was no statistical significance between the NFATc1 or TLR4-specific siRNA groups with respect to the number of osteoclasts formed.

I Number of Osteoclasts Formed

450

400

Qj 350 ~ Qj 300 U "CI ~.. 250 U c 200 ::::'" :; ::E 150 + D.. 100 ~ ~ 50

0 Control siRNA TLR4 siRNA NFATc1 siRNA Treatment Groups

Figure 23. Inhibtion of osteoclast formation mediated by siRNA. *denotes statistical significance relative to control, P<0.05.

Cultures transfected with control siRNA Cultures transfected with either NFATc1 or Figure 24. TLR4 siRNA.

51 Biological Effects of Silencing NFATc1 or TLR4 Expression on Osteoclast-

Specific Gene Expression

Osteoclast-like cells were differentiated using LPS or RANKL and tranfected with either NFATc1-specific, TLR4-specific, or control siRNA. Cells were then stimulated with LPS for an additional 72 hours. RNA was extracted and reverse transcribed into cDNA and Real time PCR (RT PCR) was performed to determine comparative mRNA expression levels of cathepsin K, tartrate- resistant acid phosphatase (TRAP), IL-6, and TNF-a relative to control gene expression. The relative expression fold change determined from the application curve of RT PCR revealed a statistically significant decrease of cathepsin K,

TRAP, IL-6, and TNF-a mRNA levels in osteoclasts treated with NFATc1 or

TLR4-specific siRNA as compared with that in the control siRNA group (P

(Figure 25). There was no statistical significance between the NFATc1 or TLR4- specific siRNA groups with respect to mRNA expression levels.

Osteoclast mRNA Expression

1.2

~ 1 c:: co o.c 'C 0.8 * * '0 • Cathepsin K !!:. c:: • TRAP .!:! O.S III I2I IL-S I ~ C. I2I TNF ~ ~ 0.4 ~ ~ &! 0.2

o Control TLR4 siRNA NFATc1 SiRNA Treatment Groups

Figure 25. Inhibition of osteoclast mRNA expression mediated by siRNA. *denotes statistical significance relative to control, P

52 Biogical Effects of Silencing NFATc1 or TLR4 Expression on Osteoclast

TNF-a Production

Osteoclast-like cells were differentiated using LPS or RANKL and tranfected with either NFATc1-specific, TLR4-specific, or control siRNA. Cells were then stimulated with LPS for an additional 72 hours. Media was collected and analyzed for TNF-a cytokine production using ELISA. Results are shown in

Table 3.

Osteoclast TNF-alpha Production

Control siRNA TLR4siRNA NFATc1 siRNA 3.8 ng/ml +1-0.29 *2.6 ng/ml +1-0.32 *1.88 ng/ml +/-0.14

Table 3. Biological effects of silencing NFATc1 or TLR4 on osteoclast TNF-a production. *denotes statistical significance relative to control, P

Analysis of Variance revealed osteoclasts in both the NFATc1-specific and

TLR4-specific siRNA groups showed a statistically significant resistance to LPS stimulation as indicated by the reduced TNF-a production compared with that in the control siRNA group (p

TNF-a production.

53 Osteoclast TNF-alpha Production

4.5

4

3.5

W 3 C, .s. 2.5 ..c:.. E- 2 cp * LL. ~ 1.5

0.5 o Control siRNA TLR4 siRNA NFATc1 siRNA Treatment groups

Figure 26. Inhibition of TNF-a production in osteoclasts mediated by siRNA. *denotes statistical significance relative to control, P<0.05.

54 Discussion

RNA interference is a conserved biologic response by which dsRNA induces the sequence-specific degradation of complementary mRNA, thereby silencing target gene expression. It has rapidly become the method of choice for studies of gene function and gene silencing experiments. We chose to independently suppress the expression of two different proteins involved in the mechanism of cytokine production and osteoclast formation. Toll-like receptors are a newly discovered class of trans-membrane receptors found on the surface of immune cells, whose activation has been shown to be critical for the initiation of inflammatory reactions induced by bacterial byproducts. TLR4 is the established receptor for LPS, which is an integral component of the cell wall of gram-negative bacteria found in the root canals of infected teeth. The relationship between LPS and periapical bone resorption has been well documented in endodontic literature. Previous studies have demonstrated the mechanisms by which LPS stimulates osteoblasts and surrounding cells to secrete pro-inflammatory cytokines such as TNF-a and IL-6 that are responsible for bone resorptive activity (Nair, 1996). More recent findings have shown that

LPS can directly stimulate osteoblasts through NF-KB activation of target genes to express RANKL, which results in the induction of osteoclast formation (Kikuchi et al., 2001). Our group was able to demonstrate that LPS can directly induce monocytes to differentiate into mature osteoclasts through a shared mechanism, yet independent from the RANK-RANKL interaction (Jiang et al., 2006). NFATc1 is the most strongly induced transcription factor gene mediated by RANKL

55 stimulation whose presence has been shown to be required during the final stage of osteoclastogenesis.

It has been previously demonstrated that antisense sequence targeting of

TLR4 inhibited TLR4 expression and reduced TNF-a release when RAW 264.7 cells were stimulated by LPS (Li et al., 2004). Our ability to successfully transfect and silence TLR4 and NFATc1 gene expression with specific siRNA in monocytes resulted in a significant reduction of LPS-induced TNF-a and IL-6 production and fewer numbers of mature osteoclasts formed. We did not observe a difference in IL-1 production, but that may be due to the fact that monocytes produce very low levels of IL-1 to begin with, as was demonstrated in the control group. We also showed that successful transfection of osteoclasts with TLR4 or

NFATc1-specific siRNA resulted in a significant reduction of osteoclast specific gene expression and lower levels of TNF-a production. Further studies using

RNAi in animal models need to be conducted in order to observe the therapeutic relevance in treatment of endodontic disease.

There are two reasons that can account for the fact that we did not obtain

100% silencing of the gene products observed: 1) This technique only blocks the expression of newly transcribed mRNA, and the observed levels may be due to residual proteins expressed by the cells prior to siRNA transfection and 2) background from mRNA or protein present in cells that were not successfully transfected will make the knockdown appear less effective than it actually is

(Zhou et al., 2006). Nonetheless, this demonstrates the potential that RNAi may have as a novel therapeutic strategy in treating endodontic disease.

56 Several other approaches have been used in the past which utilize sequence homology for the targeted inhibition of gene expression. These include Homologous Recombination, Antisense Vectors, and catalytic DNA molecules (DNAzymes) (Capecchi, 1989; Scherer and Rossi, 2003). However, due to their limited cross-species application, none show to be as promising as

RNAi (Opalinska and Gewirtz, 2002).

Currently, RNAi is most commonly used as a rapid and accurate tool for identification of gene function. Many researchers have employed this technology to elucidate the roles of individual genes in regulating cell growth, differentiation, and survival in a broad range of cell lines (Klampfer et al., 2004; Yin et al., 2004).

Other groups have deployed RNAi for the identification of potential drug targets by determining gene function and linking it to specific diseases (Nencioni et al.,

2004). This process is known as drug target discovery. These types of studies represent a powerful approach for the identification of new drug target sites by identifying a potential therapeutic target and verifying the desired effect of that target upon regulation. RNAi has also been used to dissect cellular signal transduction pathways. Cells treated with siRNA targeting a given gene can then be monitored using a microarray for the expression of other genes. Sequential targeting of various genes with siRNA makes it possible to identify genes that are associated with the target and to locate the position of each gene in a given pathway. This technology has been successfully used in determining gene function in the transforming growth factor beta (TGF-~) pathway, mitogenic

57 signaling pathway in osteoblasts, and insulin signaling (Levy and Hill, 2005;

Miguel et al., 2005; Shyu et al., 2005).

However, the greatest promise for RNAi may be in the field of clinical medicine, and its potential for therapy against a broad range of diseases.

Preliminary studies using siRNA to specifically target the HIV structural proteins

Gag and Env, the regulatory proteins Tat and Rev, the two accessory proteins

Nef and Vif, the Pol enzymes, or the viral RNA sequences in the long terminal repeat (L TR) domain have been shown to potently inhibit HIV-1 replication in human T cell lines (Jacque et al., 2002; Novina et al., 2002). In addition to targeting of the viral RNA, others have sought to inhbit viral replication using

RNAi by silencing host cell receptors such as CD4, CXCR4, and CCR5 which are essential for attachment and subsequent entry of the HIV-1 virus into the host

(Martinez et al., 2002a).

Although the majority of studies on RNAi-mediated inhibition of infectious viral diseases have focused on HIV, inhibition of viral replication by RNAi has been demonstrated in vitro for a number of other RNA viruses including hepatitis

C (HCV), poliovirus, Rous sarcoma virus (RSV), rhesus rotavirus (RRV), influenza virus, respiratory syncytial virus, dengue virus, coronavirus, as well as

DNA viruses such as human papillomavirus type 16 (HPV-16), hepatitis B (HBV), and herpes simplex virus (Gitlin and Andino, 2003; Lieberman et al., 2003).

For chronic liver inflammatory diseases such as hepatitis B and hepatitis

C, researchers have used synthetic siRNAs to target against sequences responsible for transciption and protein-coding regions of the capsid (Kapadia et

58 aI., 2003; Shlomai et al., 2003). Their results found up to a 100-fold inhibition for

HCV capsid proteins and a 6-fold decrease in secreted HBV surface antigen in the serum. HBV is the first virus whose inhibition was demonstrated in vivo using an animal model (McCaffrey et al., 2003). Thus, experimental data strongly support a role for the therapeutic potential of RNAi in the treatment of HBV and

HCV infections.

The Influenza and respiratory syncytial viruses are major causes of infection of the respiratory tract in humans. Several groups have demonstrated that synthetic siRNA targeting conserved regions of the genome, when administered by intravenous injection or via intranasal routes, could effectively inhibit virus production (Ge et al., 2004; Bitko et al., 2005; Zhang et al., 2005).

Severe acute respiratory syndrome (SARS) is a viral respiratory illness that was first reported in Asia in February 2003 and within a few months spread to more than two dozen countries in North America, South America, Europe, and Asia.

According to the World Health Organization (WHO), a total of 8,098 people worldwide became sick and 774 died. A recent study has reported the use of siRNAs in prophylactic and therapeutic regimens targeting the SARS coronavirus

(SCV) in a Rhesus macaque model (Li et al., 2005a). Their analysis revealed that siRNAs significantly reduced SARS-like symptoms, diminished SCV viral levels, and reduced alveoli damage without any evidence of siRNA-induced toxicity.

Currently, there is growing enthusiasm regarding the potential therapeutic applications of RNAi for cancer. Most human tumors arise from genetic mutations in genes that encode for proteins regulating cell division, which results in

59 uncontrolled cellular growth and differentiation. Thus, the ability to target the mutant gene and selectively down regulate expression of abnormal proteins without affecting the wild-type counterpart provides an attractive and promising tool in gene therapy. Multiple groups have successfully demonstrated siRNA­ induced silencing of cancer-associated genes in vitro. Mutations of the ras protooncogene are present in a variety of cancers. One study showed the ability to specifically silence the mutant ras oncogene without affecting the wild-type copy (Brummelkamp and Bernards, 2003). Other preclinical studies have shown growth inhibition and apoptosis of cancer cells by RNAi-mediated suppression of various critical oncogenes or tumor-promoting genes, such as vascular endothelial growth factor (VEGF), human telomerase (hTR), viral oncogenes

(HPV E6), or translocated oncogenes (bcr-abl) (Butz et al., 2003; Kosciolek et al.,

2003; Scherr et al., 2003; Zhang et al., 2003). Various other in vivo studies have also effectively utilized RNAi in cases of brain, breast, and ovarian cancer to reduce tumor formation in animal models (Menendez et a/., 2004; Boado, 2005;

Onodera et al., 2005).

However, similar to other forms of gene-based therapies, there are several problems associated with the development of siRNA therapeutics. The primary obstacle is the in vivo delivery of these small molecules to the desired cell type, tissue, or organ. Because of their relatively large molecular mass and high negative charge, RNAs have difficulty crossing the cell membrane on their own.

Two different approaches have been developed to address this concern-1) direct introduction of chemically modified synthetic siRNAs enhanced for

60 improved pharmacokinetic properties or 2) the use of plasmid or viral vectors containing DNA templates to express siRNA within cells.

Synthetic siRNAs may best be suited for short-term interventions and in situations in which long-term silencing is not necessary, such as in treatment of acute viral infections or silencing of pro-inflammatory host molecules in order to prevent tissue damage (Le. apical periodontitis). In cells that are terminally differentiated or slow to divide, such as macrophages or osteoclasts, gene suppression by exogenously administered synthetic siRNA can last up to several weeks, yet their effect in cells that undergo rapid division is more short-lived

(peaking within 2-3 days, and gone by 1 week), as a result of continuous dilution of the siRNA with each cell division (Song at a/., 2003). However, the half-life of unmodified siRNAs in serum is very short (reports vary from minutes to days), and their cellular uptake is not ideal. The short half-life is primarily due to their rapid elimination by renal filtration due to their small size (-7kDa) and degradation by endogenous ribonuclease digestion. Thus, the bioavailability of unmodified siRNAs is limited under characteristic in vivo conditions, and gene silencing levels are likely to be insignificant. For this reason, numerous attempts

have been made to chemically modify siRNAs in order to decrease their susceptibility to serum nuclease attack without sacrificing biological activity, allowing them to maintain sufficient gene-silencing activity for therapeutic use

(Amarzguioui at a/., 2003; Braasch at a/., 2003; Chiu and Rana, 2003).

Chemical modifications can easily be placed at the terminal ends, within the backbone, or at the ribose molecules of the siRNA duplex {de Fougerolles at

61 al., 2005). Particularly, phosphorothioate modification of the internucleoside linkage has been shown to improve nuclease stability and is well tolerated within the siRNA duplex (Levin, 1999; Harborth et al., 2003). Encapsulation of siRNAs in lipid complexes or liposomes, coupling to fusogenic peptides, or linkage to antibodies or cell surface receptor ligands may also facilitate better entry into cells and improve biodistribution by producing potential drug candidates that are big enough to bypass rapid filtration by the kidney (Manoharan, 2002). Recently, chemically modified siRNAs covalently linked to cholesterol were shown to improve binding to blood components, thereby increasing the circulation time of the siRNAs, and increase delivery to hepatocytes (Lorenz et al., 2004; Soutschek et al., 2004). A dinitrophenol modification at the terminal ends has been shown to improve transfection efficiency and enhance intracellular stability in vitro (Liao and Wang, 2005), and perhaps, of most interest to researchers, peptide­ conjugates have shown to improve cell permeation properties as well as sequence-specific targeting (Juliano, 2005). However, chemically synthesized siRNAs are expensive, which poses some difficulty, when genome-wide RNAi screens are considered in mammalian cells.

In order to circumvent some of the issues involved with direct siRNA transfection, several groups have developed vector-based delivery systems that mediate the production of stable siRNA-like molecules in mammalian cells

(Brummelkamp et al., 2002; Paddison et al., 2002; Paul et al., 2002). Viral vectors derived from adenovirus, adeno-associated virus, retrovirus, or lentivirus can be used for more long-term gene silencing, which would be more effective

62 for the treatment of chronic infections such as HIV or hepatitis C. These vectors are engineered to use RNA-polymerase III promoters to direct the synthesis of short hairpin RNA (shRNA) molecules, which are intracellularly processed into molecules resembling siRNA that are identical in sequence to the mRNA being targeted for suppression. Vector-based production of shRNA in vivo have been shown to be as effective as in vitro generated synthetic siRNA in suppressing gene expression, and, additionally, can be used to observe loss-of-function phenotypes that take longer periods of time to develop (Brummelkamp et a/.,

2002a; Rubinson et a/., 2003; Scherr et a/., 2003a).

Although great progress has been made in the development of gene­ therapy vectors, there are still a number of concerns about safety and control of gene expression associated with vector-delivered gene therapy (Thomas et a/.,

2003). These include efficient transduction of targeted cells, sustained and efficient gene expression of transduced cells, the danger of malignant transformation resulting from insertional mutagenesis, as well as host immune or inflammatory responses to the viral vector itself. Furthermore, the effect of long­ term expression of shRNA in mammalian cells is unknown.

Even though the original studies of siRNA silencing suggested high specificity, several mechanisms have been described with both synthetic and vector-based siRNA expression that can lead to unintended effects on gene expression and other unexpected "side effects", all of which need to be carefully considered when developing RNA-based therapies (Jackson et a/., 2003;

Jackson and Linsley, 2004). One potential complication is that siRNA has the

63 ability to trigger the innate immune system. Induction of an interferon response could potentially cause a global and nonspecific suppression of protein translation, particularly in highly sensitive reporter cell lines at high concentrations of siRNAs (Sledz et al., 2003). However, interferon response is typically induced when the double stranded RNA molecule is greater than 30 base pairs (McManus and Sharp, 2002), which is longer than the 21-23 nt in length siRNA used in RNA interference. Another possible source of toxicity might come from the recognition and binding of siRNAs by Toll-like receptor 3, which is also a pattern recognition receptor found on immune cells. Upon recognition of double stranded RNA molecules, TLR 3 triggers a danger signal reaction and initiates a pro-inflammatory response (Kariko et al., 2004). Yet, chemical modifications of siRNA may be enough to overcome TLR 3 recognition and signaling, and fortunately, these problems have not been observed in most animal studies.

Perhaps a more significant problem associated with siRNA is unanticipated "off-target" effects resulting from mRNA cleavage or translational repression of genes bearing partially complementary sequences to either strand of the duplex siRNA. It. was originally believed that siRNA requires almost complete homology throughout the length of its sequence with the intended mRNA target for effective RNAi to occur. However, it now appears that as few as eleven contiguous complementary base pairs of siRNA may be enough to evoke the off-target effect of RNAi-mediated silencing (Jackson, 2003). Although short stretches of homology are often inevitable, care must be taken to avoid longer

64 stretches which have more considerable effects on gene expression. It is also possible, in some cases, for the siRNA sense strand to be preferentially selected by the RISC complex instead of the antisense strand, resulting in inhibition of an unintended mRNA target (Jackson et al., 2003). However, it may be feasible to inhibit activity of the sense strand through chemical modification, while maintaining the functionality of the antisense strand, therefore eliminating this potential problem (Khvorova et al., 2003; Schwarz et al., 2003; Reynolds et al.,

2004). Furthermore, a recent study found that the majority of off-target effects associated with nonspecific silencing of gene expression resulted from the lipid­ based transfection reagent and not the siRNA (Fedorov et al., 2005). This is in agreement with others who showed lack of interferon response in mice upon injection of naked siRNAs (Heidel et al., 2004). Nonetheless, these issues highlight the importance of judicious siRNA design and testing of different sequences in order to choose the one with the best target-specific/off-target profile. This can be achieved by taking advantage of the wide-ranging databases of expressed mRNAs that are currently available. A BLAST search

(http.1lwww.ncbi.nlm.nih.govIBLASD should be performed to identify the most effective siRNA sequences and to make certain that the sequence is homologous to the target gene of interest. Additionally, microarray screens should be used to monitor genome-wide expression profiles (Clarke et al., 2004).

Although it is clear that more progress needs to be made to improve

RNAi-delivery systems and to evaluate off-target effects and other potential sources of toxicity, it is encouraging to note that there are more than 30

65 pharmaceutical and biotechnology companies that have stated interest in or currently have an RNAi-based drug development program in progress, and many have published preliminary data obtained from in vivo and mammalian model systems validating their projects. Sirna Therapeutics recently completed a Phase

I study of Sirna-027, which is a chemically modified siRNA drug that targets

VEGFR1 in order to treat age-related macular degeneration (AMD), results from which were reported at the American Society of Gene Therapy conference in

June 2005 (Whelan, 2005). They have also collaborated with Protiva

Biotherapeutics for work relating to treatment of hepatitis B infection (Morrissey et al., 2005; Morrissey et al., 2005b). Alnylam Pharmaceuticals has partnered with Norvartis, Merck, and Medtronic for drug development projects targeting multiple diseases, and has published preliminary results using anti-ApoB siRNAs for treatment of hypercholesterolemia (Soutschek et al., 2004). Their next target is pandemic influenza, for which they filed an Investigational New Drug

Application (IND) with the Food and Drug Administration (FDA) in 2006. Nastech

Pharmaceuticals, working in conjunction with the Mayo Clinic, presented preclinical results at the November 2005 American College of Rheumatology meeting on the use of an anti-TNF-a siRNA for treatment of rheumatoid arthritis

(Behlke, 2006). Calando Pharmaceuticals has collaborated with the Children's

Hospital of Los Angeles to describe the use of siRNA to treat Ewing's sarcoma

(Hu-Lieskovan et al., 2005). Numerous studies have been published by

Intradigm, in collaboration with other pharmaceutical companies, using siRNA to treat cancer, arthritis, ocular, and viral diseases (Kim et al., 2004; Schiffelers et

66 al., 2004; Li et al., 2005; Schiffelers et al., 2005; Schiffelers et al., 2005b), and

Abbott and NeoPharm have both investigated the potential of siRNA-based therapeutics in a murine cancer model system (Li et al., 2005; Pal et al., 2005).

However, it should be noted that Fomiversen (Vitravene) manufactured by ISIS

Pharmaceuticals, which is a drug for the treatment of CMV retinitis, is the only existing FDA-approved siRNA-based drug available on the market at this time.

Not enough may be known about the potential negative effects of prolonged or repetitive use of RNAi on normal cellular metabolism when used for treatment of chronic diseases. It is possible that toxicities may not show up for months, or perhaps years. Clearly, such issues require further long-term studies in therapeutically relevant animal models of RNA interference. Nonetheless, considering the immense interest and the rapid pace by which RNAi research is advancing, it is foreseeable that this relatively new scientific discovery will have a dramatic impact on the development of an innovative and new class of drugs whose therapeutic potential seems enormous.

67 Conclusion

RNA interference is a unique and powerful tool that can be used for the study gene function by suppressing its expression. It is also a fast and inexpensive method to selectively silence a gene product in complex biological systems whose clinical potential for treatment of various diseases and disorders has been demonstrated. Using RNAi, with specific NFATc1 and TLR4 siRNA we were able to successfully:

1. Deliver siRNA into the cytoplasm of monocytes and osteoclasts with high efficiency. 2. Demonstrate a significant reduction in the expression of TLR4 and NFATc1 in cells that were transfected with specific siRNA. 3. Demonstrate a significant reduction of TNF-a and IL-6 production in transfected monocytes in response to LPS stimulation. 4. Demonstrate a significant reduction in the number of mature osteoclasts formed in response to LPS stimulation. 5. Demonstrate a significant reduction in osteoclast specific gene expression and lower levels of TNF-a production in response to LPS stimulation.

Although much work still remains in improving the delivery, specificity, and effectiveness of siRNAs, RNAi-based therapies have emerged as highly promising prospects with applications for a wide spectrum of diseases.

68 Statistical Analysis

Oneway analysis of variance for IL-6 ELISA in monocytes

Descriptives

Final (uQ/ml) 95% Confidence Interval for Mean Std. Std. Lower Upper N Mean Deviation Error Bound Bound Minimum Maximum control 3 9.52000 2.047144 1.181919 4.43461 14.60539 7.180 10.980 TLR4 3 3.48000 .784602 .452990 1.53094 5.42906 2.580 4.020 NFATc1 3 5.11333 .984344 .568311 2.66809 7.55858 4.420 6.240 Total 9 6.03778 2.960548 .986849 3.76210 8.31346 2.580 10.980

Test of Homogeneity of Variances

Final (ug/ml) Levene Statistic df1 df2 Sig. 3.246 2 6 .111

ANOVA

Final (ug/ml) Sum of Squares df Mean Square F Sig. Between Groups 58.568 2 29.284 15.212 .004 Within Groups 11.551 6 1.925 Total 70.119 8

69 Post Hoc Tests for IL-6 production in monocytes

Multiple Comparisons

DeDendent Variable: Final (uQ/ml)

Mean Difference 95% Confidence Interval (I) LPS + (J) LPS + (I-J) Std. Error Sig. Lower Bound Upper Bound Tukey HSD control TLR4 6.040000· 1.132876 .004 2.56403 9.51597 NFATc1 4.406667· 1.132876 .019 .93069 7.88264 TLR4 control -6.040000· 1.132876 .004 -9.51597 -2.56403 NFATc1 -1 .633333 1.132876 .380 -5.10931 1.84264 NFATc1 control -4.406667* 1.132876 .019 -7.88264 -.93069 TLR4 1.633333 1.132876 .380 -1 .84264 5.10931 LSD control TLR4 6.040000· 1.132876 .002 3.26795 8.81205 NFATc1 4.406667· 1.132876 .008 1.63462 7.17871 TLR4 control -6.040000· 1.132876 .002 -8.81205 -3.26795 NFATc1 -1 .633333 1.132876 .199 -4.40538 1.13871 NFATc1 control -4.406667* 1.132876 .008 -7.17871 -1 .63462 TLR4 1.633333 1.132876 .199 -1.13871 4.40538 *. The mean difference is significant at the .05 level.

Homogeneous Subsets (IL-6 production in monocytes)

Final (ug/ml)

Subset for alpha = .05 LPS + N 1 2 Tukey Hsoa TLR4 3 3.48000 NFATc1 3 5.11333 control 3 9.52000 Sig. .380 1.000 Means for groups in homogeneous subsets are displayed. a. Uses Harmonic Mean Sample Size = 3.000.

Graph (IL-6 production in monocytes)

~, ,. c. " ~ ,0- IL UJ en N .; 8 .,.. I .; 6 c( en ::; UJ

control siRNA TlR" siRNA NFATc1 siRNA LPS+

70 Oneway analysis of variance TNF - alpha ELISA in monocytes

Descriptives

Final (ug/ml\ 95% Confidence Interval for Mean Std. Std. Lower Upper N Mean Deviation Error Bound Bound Minimum Maximum control 3 23.49000 .980064 .565840 21.05539 25.92461 22.695 24.585 siRNA TLR4 3 15.16500 1.005336 .580431 12.66761 17.66239 14.145 16.155 siRNA NFATc1 3 18.31000 1.429047 .825061 14.76005 21.85995 16.725 19.500 siRNA Total 9 18.96633 3.775642 1.256614 16.08596 21.89070 14.145 24.585

Test of Homogeneity of Variances

Final (ug/ml) Levene Statistic df1 df2 Sig. .445 2 6 .660

ANOVA

Final (ug/ml) Sum of Squares df Mean Square F Sig. Between Groups 106.029 2 53.015 39.628 .000 Within Groups 8.027 6 1.338 Total 114.056 8

71 Post Hoc Tests for TNF-alpha production in monocytes

Multiple Comparisons

Dependent Variable: Final (ug/ml)

Mean Difference 95% Confidence Interval (I) LPS + (J) LPS + (I-J) Std. Error Sig. Lower Bound Upper Bound Tukey HSD control siRNA TLR4siRNA 8.325000· .944387 .000 5.42736 11 .22264 NFATc1 siRNA 5.180000· .944387 .004 2.28236 8.07764 TLR4 siRNA control siRNA -8.325000· .944387 .000 -11.22264 -5.42736 NFATc1 siRNA -3.145000· .944387 .036 -6.04264 -.24736 NFATc1 siRNA control siRNA -5.180000· .944387 .004 -8.07764 -2 .28236 TLR4siRNA 3.145000· .944387 .036 .24736 6.04264 LSD control siRNA TLR4siRNA 8.325000· .944387 .000 6.01417 10.63583 NFATc1 siRNA 5.180000· .944387 .002 2.86917 7.49083 TLR4 siRNA control siRNA -8.325000· .944387 .000 -10.63583 -6 .01417 NFATc1 siRNA -3.145000· .944387 .016 -5.45583 -.83417 NFATc1 siRNA control siRNA -5.180000· .944387 .002 -7.49083 -2.86917 TLR4siRNA 3.145000· .944387 .016 .83417 5.45583 •. The mean difference IS Significant at the .05 level.

Homogeneous Subsets (TNF-alpha production in monocytes)

Final (ug/ml)

Subset for alpha =. 05 LPS + N 1 2 3 Tukey HSDa TLR4 siRNA 3 15.16500 NFATc1 siRNA 3 18.31000 control siRNA 3 23.49000 Sig. 1.000 1.000 1.000 Means for groups in homogeneous subsets are displayed. a. Uses Harmonic Mean Sample Size =3.000.

Graph (TNF-alpha production in monocytes)

;;; 26 .: u. w en 2' N .t- o!!! 22 I ..> ~= ~..§ 20 -'"...J::I w-.. .s:: 1S- Eo '1' u. Z 16- I !::. ..c: :::IE 14 I control siRNA TlR4 siRNA NFATc1 siRNA LPS +

72 Oneway analysis of variance IL-1 alpha ELISA in monocytes

Descriptives

Dilution value 95% Confidence Interval for Mean Std. Std. Lower Upper N Mean Deviation Error Bound Bound Minimum Maximum control 3 30.6667 3.21455 1.85592 22.6813 38.6521 27.00 33.00 siRNA TLR4 3 25.6667 3.78594 2.18581 16.2619 35.0715 23.00 30.00 siRNA NFATc1 3 32.6667 2.51661 1.45297 26.4151 38.9183 30.00 35.00 siRNA Total 9 29.6667 4.18330 1.39443 26.4511 32.8822 23.00 35.00

Test of Homogeneity of Variances

Dilution value Levene Statistic df1 df2 Sig. .589 2 6 .584

ANOVA

Dilution value Sum of Squares df Mean Square F Sig. Between Groups 78.000 2 39.000 3.774 .087 Within Groups 62.000 6 10.333 Total 140.000 8

73 Post Hoc Tests for IL-1-alpha production in monocytes

Multiple Comparisons

Dependent Variable: Dilution value

Mean Difference 95% Confidence Interval (I) LPS + (J) LPS + (I-J) Std. Error Sig. Lower Bound U~er Bound Tukey HSD control siRNA TLR4 siRNA 5.00000 2.62467 .217 -3.0532 13.0532 NFATc1 siRNA -2.00000 2.62467 .738 -1 0.0532 6.0532 TLR4 siRNA control siRNA -5.00000 2.62467 .217 -13.0532 3.0532 NFATc1 siRNA -7. 00000 2.62467 .083 -15.0532 1.0532 NFATc1 siRNA control siRNA 2.00000 2.62467 .738 -6.0532 10.0532 TLR4 siRNA 7.00000 2.62467 .083 -1.0532 15.0532 LSD control siRNA TLR4 siRNA 5.00000 2.62467 .105 -1.4223 11.4223 NFATc1 siRNA -2.00000 2.62467 .475 -8.4223 4.4223 TLR4 siRNA control siRNA -5. 00000 2.62467 .105 -11.4223 1.4223 NFATc1 siRNA -7.00000' 2.62467 .037 -13.4223 -.5777 NFATc1 siRNA control siRNA 2.00000 2.62467 .475 -4.4223 8.4223 TLR4 siRNA 7.00000' 2.62467 .037 .5777 13.4223 '. The mean difference IS Significant at the .05 level.

Homogeneous Subsets (IL-1-alpha production in monocytes)

Dilution value

Subset for alpha = .05 LPS + N 1 Tukey Hsoa TLR4 siRNA 3 25.6667 control siRNA 3 30.6667 NFATc1 siRNA 3 32.6667 Sig. .083 Means for groups in homogeneous subsets are displayed. a. Uses Harmonic Mean Sample Size =3.000.

Graph (IL-1-alpha production in monocytes)

c: ..0 36- ~ 0 -- UI en 33 +.. a; 30- -- .,.,> -" I ....en > ::; 27 - '- UI .r=.. Q.

.. 2. ~ c: .. -'- ., 21 :::E

control siR NA nR4 s1RNA NFATcl siRNA LPS+

74 Oneway - Number of Osteoclasts Formed

Oescriptives

Osteoclasts formed 95% Confidence Interval for Std. Mean N Mean Deviation Std. Error Lower Bound Upper Bound Minimum Maximum control siRNA 3 356.0000 24.87971 14.36431 294.1954 417.8046 329.00 378.00 TLR4 siRNA 3 234.0000 57.88782 33.42155 90.1987 377.8013 188.00 299.00 NFATcl siRNA 3 152.0000 39.00000 22.51666 55.1186 248.8814 128.00 197.00 Total 9 247.3333 96.31070 32.10357 173.3024 321.3643 128.00 378.00

AN OVA

Osteoclasts formed Sum of Squares df Mean Square F Sig. Between Groups 63224.00 2 31612.000 17.271 .003 Within Groups 10982.00 6 1830.333 Total 74206.00 8

Post Hoc Tests for Number of Osteoclasts Formed

Multiple Comparisons

Dependent Variable: Osteoclasts formed

Mean Difference 95% Confidence Interval (I) LPS + (J) LPS + (I-J) Std. Error Sig. Lower Bound Upper Bound Tukey HSD control siRNA TLR4 siRNA 122.00000' 34.93168 .030 14.8200 229.1800 NFATcl siRNA 204.00000' 34.93168 .003 96.8200 311.1800 TLR4 siRNA control siRNA -122.00000' 34.93168 .030 -229.1800 -14.8200 NFATcl siRNA 82.00000 34.93168 .124 -25.1800 189.1800 NFATcl siRNA control siRNA -204.00000' 34.93168 .003 -311.1800 -96.8200 TLR4 siRNA -82.00000 34.93168 .124 -189.1800 25.1800 LSD control siRNA TLR4 siRNA 122.00000' 34.93168 .013 36.5253 207.4747 NFATcl siRNA 204.00000' 34.93168 .001 118.5253 289.4747 TLR4 siRNA control siRNA -122.00000' 34.93168 .013 -207.4747 -36.5253 NFATcl siRNA 82.00000 34.93168 .057 -3.4747 167.4747 NFATcl siRNA control siRNA -204.00000' 34.93168 .001 -289.4747 -118.5253 TLR4 siRNA -82.00000 34.93168 .057 -167.4747 3.4747 '. The mean difference IS significant at the .05 level.

75 Homogeneous Subsets

Osteoclasts formed Subset for alpha = .05 LPS + N 1 2 Tukey HSDs NFATc1 siRNA 3 152.0000 TLR4 siRNA 3 234.0000 control siRNA 3 356.0000 Sig. .124 1.000 Means for groups in homogeneous subsets are displayed. a. Uses Harmonic Mean Sample Size =3.000.

Oneway - Osteoclast TNF-alpha level

Descriptives

TNFalpha levels al for Std. Mean N Mean Deviation St er Bound Minimum Maximum control siRNA 3 3.8000 .28844 .16653 3.0835 4.5165 3.48 4.04 TLR4 siRNA 3 2.6000 .31749 .18330 1.8113 3.3887 2.24 2.84 NFATc1 siRNA 3 1.8800 .13856 .08000 1.5358 2.2242 1.80 2.04 Total 9 2.7600 .86971 .28990 2.0915 3.4285 1.80 4.04

ANOVA

TNF aipiI h a Ieves Sum of Squares df Mean SQuare F Sig. Between Groups 5.645 2 2.822 41.669 .000 Within Groups .406 6 .068 Total 6.051 8

76 Post Hoc Tests for Osteoclast TNF-alpha Production

Multiple Comparisons

Dependent Variable: TNFalpha levels

Mean Difference 95% Confidence Interval (I) LPS+ (J) LPS + (I.J) Std. Error Sig. Lower Bound Upper80und Tukey HSD control siRNA TLR4siRNA 1.20000' .21250 .003 .5480 1.8520 NFATc1 siRNA 1.92000' .21250 .000 1.2680 2.5720 TLR4 siRNA control siRNA -1.20000' .21250 .003 ·1.8520 -.5480 NFATc1 siRNA .72000' .21250 .034 .0680 1.3720 NFATc1 siRNA control siRNA -1.92000' .21250 .000 -2.5720 -1.2680 TLR4 siRNA -.72000' .21250 .034 -1.3720 -.0680 LSD control siRNA TLR4 siRNA 1.20000' .21250 .001 .6800 1.7200 NFATc1 siRNA 1.92000' .21250 .000 1.4000 2.4400 TLR4 siRNA control siRNA -1.20000' .21250 .001 -1.7200 -.6800 NFATc1 siRNA .72000' .21250 .015 .2000 1.2400 NFATc1 siRNA control siRNA -1.92000' .21250 .000 ·2.4400 -1.4000 TLR4 siRNA -.72000' .21250 .015 -1.2400 -.2000 '. The mean difference IS significant at the .05 level.

Homogeneous Subsets

TNFalpha levels

Subset for alpha = .05 LPS + N 1 2 3 Tukey HSDa NFATc1 siRNA 3 1.8800 TLR4 siRNA 3 2.6000 control siRNA 3 3.8000 Sig. 1.000 1.000 1.000 Means for groups in homogeneous subsets are displayed. a. Uses Harmonic Mean Sample Size::: 3.000.

77 Graph (Osteoclast TNF-alpha Production)

-,--

.!!! Q) 4 > ~ cu ~ Q. -.-- cu u.. Z -l....- I- e.> ~ It) ." -l....- I I I I control siRNA TLR4 siRNA NFATc1 siRNA LPS+

Graph (Osteoclasts Formed)

400

o -2 3 III I ~ U o ~ III 0 2 e.>

control siRNA TLR4 siRNA NFATc1 siRNA LPS+

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